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Currently every day in the USA 1000 people die of sudden cardiac arrest (SCA)outside of hospitals or ambulances - before emergency medical help arrives - inthe streets, workplaces, schools and homes of our cities, adults and children.Brain death commences in 3 minutes, and often the ambulance just can't be therein time. Citizen cardiopulmonary resuscitation (CPR) and automated externaldefibrillator (AED) use can save precious minutes and lives. Using publicaccess AED's saves lives in SCA- however AEDs are used in <2% of cardiacarrests, though could save lives in 80% if available, findable, functioning,and used. The systems problem to solve is that there is no comprehensive orreal time accessible database of the AED locations, and also it is not knownthat they are actually being positioned where they are needed. The iRescUproject is designed to bridge this gap in SCA survival, by substantiallyaugmenting the AED database. Utilizing a combination of AED crowd sourcing andgeolocation integrated with existing 911 services and SCA events and projectedevents based on machine learning data information to help make the nearest AEDaccessible and available in the setting of a SCA emergency and to identify theareas of greatest need for AEDs to be positioned in the community. Helping tosave lives and address preventable death with a social good approach andapplied big data.

iRescU - Data for Social Good Saving Lives Bridging the Gaps in Sudden Cardiac Arrest Survival